Open AccessIntelligent Information Retrieval Using Hybrid of Fuzzy Set and Trust
Author(s) -
Suruchi Chawla
Publication year - 2017
Publication title -
oriental journal of computer science and technology
Language(s) - English
Resource type - Journals
eISSN - 2320-8481
pISSN - 0974-6471
DOI - 10.13005/ojcst/10.02.09
Subject(s) - computer science , information retrieval , set (abstract data type) , query expansion , web query classification , session (web analytics) , result set , web search query , data mining , search engine , fuzzy logic , world wide web , artificial intelligence , programming language
The main challenge for effective web Information Retrieval(IR) is to infer the information need from user’s query and retrieve relevant documents. The precision of search results is low due to vague and imprecise user queries and hence could not retrieve sufficient relevant documents. Fuzzy set based query expansion deals with imprecise and vague queries for inferring user’s information need. Trust based web page recommendations retrieve search results according to the user’s information need. In this paper an algorithm is designed for Intelligent Information Retrieval using hybrid of Fuzzy set and Trust in web query session mining to perform Fuzzy query expansion for inferring user’s information need and trust is used for recommendation of web pages according to the user’s information need. Experiment was performed on the data set collected in domains Academics, Entertainment and Sports and search results confirm the improvement of precision.